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smithery.ai

bilibili-up-batch

批量下载 B 站 UP 最近 N 条视频到 imports，并用 video_pipeline 生成证据?

Installation

$ npx skills add https://smithery.ai
View on skills.sh ↗

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Skill metadata

Parsed from SKILL.md frontmatter.

Allowed toolsvideo_pipeline, workspace, shell, python

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,091 B
  • docs SUMMARY.md 154 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

触发条件

当用户给出一个 B 站 UP 主页（space.bilibili.com/<mid> 或 b23.tv 短链），并要求“拉取最近 N 条视频并批处理”为研究资产时使用。

目标

  1. 下载：把最新 N 条视频下载到 imports/content/videos/bilibili/<mid>/
  2. 分析：对每个视频运行 videopipeline，产出 state/video-analyses/<analysisid>/evidence.json 与 evidence_compact.md
  3. （可选）后续由 digest-content 读取 evidence_compact.md 生成 digest 并归档到 topic

依赖

  • ffmpeg（系统已安装即可）
  • yt-dlp（建议安装到仓库 venv：.venv/bin/python -m pip install yt-dlp）

硬约束

  • 不在 git 里提交下载的视频文件（imports/ 默认不入 git）
  • video_pipeline 只处理本地文件；下载是独立步骤
  • 不写入任何 cookie/token 到仓库（如需登录态下载，只允许通过环境变量/本地配置注入）

SOP（推荐用 worker panes）

  1. Controller pane（主控）先设置接收通知

- 运行：scripts/tmuxsetcontroller_pane.sh

  1. Worker pane：批量下载 + 分析

- 对单个 UP（最近 30 条）： - python3 scripts/bilibiliupbatch.py --up '<spaceorb23url>' --limit 30 --download --analyze --enable-ocr - 若你要节省时间（先跑转写，稍后再 OCR）： - python3 scripts/bilibiliupbatch.py --up '<spaceorb23url>' --limit 30 --download --analyze

  1. Worker 完成后通知 controller

- scripts/tmuxnotifycontrollerdone.sh --topic <topicid或占位> --record <state/runs/...json> --status done

  1. 生成 digest（可选但推荐）

- 对每个 state/video-analyses/<analysisid>/evidencecompact.md 使用 digest-content 生成 digest； - 如需归档到 topic：再用 topic-ingest 更新 sources.md/timeline.md。